1. Field
Embodiments of the invention relate to fast, dynamic, data-driven report deployment of data mining and predictive insight into Business Intelligence (BI) tools.
2. Description of the Related Art
Data mining results and insights are different from data that is typically stored in flat table structures. Therefore, the data mining results and insights are mostly stored as data mining models (also referred to as “mining models”) in hierarchical ways in large documents (e.g. standardized Predictive Model Markup Language (PMML) format). However, many conventional Business Intelligence (BI) tools can not consume those data mining models. BI tools may be described as analyzing data and presenting reports (e.g. report design tools). Therefore, the mining results and insights need to be transformed to a form that is consumable by the BI tools.
Few vendors provide dedicated BI tools (e.g. report design tools) in which a report designer can manually create mining results and insights reports (i.e. mining reports). Because vendors do not provide dedicated BI tools, the user has to transform mining results and insights into a form consumable by the BI Tools. Further, deep data mining knowledge is required to create reports with the general BI tools. Nevertheless, the creation of such reports is a tedious task and changes in the underlying data result in long lasting manual changes. Further, the task of transforming the mining results and insights and creating the reports and meta information requires deep knowledge in the involved tools and software, as well as, deep mining skills to know how to visualize those mining insights.
Known solutions are based on exporting images that were generated within the mining tool. Then, the images are incorporated into the report in a static manner (e.g. similar to using an image within a web page). However, this is a very static and non-interactive way. Further, this solution does not provide automatic deployment of the mining results and insights.
Most tools do not allow visualizing standardized data mining models natively. Thus, such tools are less flexible and restrict the visualization to predefined graphics.